The term “management” refers to the archiving of the data (meaning the storage of the data in persistent memory), the reproduction (display) and the deletion of the data from the data memory, as well as the sorting and finding of particular data from the data memory in accordance with predetermined criteria (browsing).
The term “processing” may refer to the modification (editing/preparation) of the data.
The data of the medical facility to be managed and processed includes patient data, works/tasks or worklists for the personnel of the medical facility and medical image data.
The management of such medical data is increasingly undertaken with the support of computers by server systems, e.g., so-called information systems. An information system includes: (1) one or more data memories, e.g., in the form of a storage area network (SAN); (2) one or more associated data servers; (3) at least one relational database that is implemented in a database server; (4) one or more further servers, for example, in which methods for database access and data processing are implemented.
Different medical information systems have established themselves in the medical field for the different types of data. Thus, in the environment of a medical facility, such as a clinic for example, a Hospital Information System (HIS) is used for the management and processing of patient data, and a Radiology Information System (RIS) is used for scheduling radiological examinations, supporting the diagnosis of medical imaging data and documentation of the diagnoses. In addition, the IT structure of a hospital may include a so-called Picture Archiving and Communication System (PACS) for archiving and communicating medical image data on the basis of the DICOM standard as well as an Advanced Visualization (AV) system that provides server-supported functions for visualizing volume data, e.g., dynamic volume rendering.
The aforementioned server systems, in this case, are as a rule present in parallel to one another. This demands a high outlay in procurement and maintenance, which is barely affordable, in particular for small medical facilities or any other facility with a comparatively low finance volume.
The complex IT structure of a modern medical facility described above also has only comparatively poor scaling properties. Adapting such an IT structure to greater changes in the volume of data to be processed and archived and/or to the required computing power is thus mostly only possible with a comparatively high outlay.
Personal computers (PCs) have previously predominantly been used as users or terminals (classically referred to as clients) of such an IT structure, wherein these PCs are often embodied as so-called thin clients that obtain a majority of their required processing power from a connected server. In recent times, however, there has been an increasing desire also to use mobile small computers such as smartphones, tablets, or PDAs as the user device.
A further problem of conventional information systems in the medical environment lies in the fact that the front-end software of these systems may be specifically and rigidly oriented to the management and processing of specific data types. This leads to the front end having to be programmed and maintained separately for each information system. This, in its turn, may render the integration of innovative user devices such as smartphones and tablets into the clinical workflow more difficult, since the diversification of the software components connected with the corresponding adaptation of the respective front end is only able to be managed at great expense in respect of its production and further development. This may relate to software for display (e.g., referred to as viewing) of image data, since corresponding applications have to be provided for different image data types and also for different purposes, e.g., preliminary examination of the image data at the modality producing the image (examination), the actual diagnosis (reading) and, if necessary, just browsing.
In recent years, so-called cloud solutions have become established as an alternative to conventional client-server architectures. In such cases, a cloud is understood to be a data processing facility, which on the one hand is provided and operated by a cloud vendor independent of the user. The cloud vendor provides a plurality of users with the hardware and, if necessary, the software of the cloud as a service within the framework of a usage agreement (e.g., subscription). Depending on the scope of the services provided, a distinction is made between the following: (1) A usage pattern referred to as an “Infrastructure as a Service” (IaaS) in which the user is merely provided with computer hardware (computers, networks and memory) of the cloud, while the users themselves are fully responsible for the software operated in the cloud; (2) A usage pattern described as a “Platform as a Service” (PaaS) in which the user is offered from the cloud the computer hardware together with a programming and runtime environment building thereon, so that users themselves are only responsible for the application software (applications) implemented in this programming and runtime environment; and (3) A usage pattern designated as “Software as a Service” (SaaS), in which specific application software is also made available to the user from the cloud.
Depending on the group of users to which the respective cloud is addressed, a further distinction is made between the following: (1) What is referred to as public cloud, of which the services may be made use of by anyone; and (2) What is referred to as a private cloud, which is only accessible to users of a specific organization, e.g., of a specific company.
For each user of a public cloud, the access permissions are regulated to specific hardware and software components of the cloud by the subscription assigned to the user. This means that public clouds are regularly multi-tenant. This identifies the capability of keeping data, user management, and computing operations strictly separated for users with different subscriptions. A user of the public cloud may thus not view the data, user management, and computing operations of another user with a different subscription and also cannot influence this data.
However, the problems described above are not solved by merely transferring the classically conventional server systems into the cloud, since the complexity of the IT structure is not simplified by this, but instead is even increased. On the other hand, new problems arise because of this. In particular, the relocation of the IT structure into the cloud may result in perceptible increases of the latency times for responding to user queries. This may be tedious in viewing applications for displaying medical image data, since, conditional on latency times, the construction of the images to be viewed may perceptibly lag behind the working tempo of a user, which may lead to a marked adverse effect on the work sequences in the medical environment.